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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Martijn Vlaar ()
Alfred Schouten ()
Alistair Vardy ()
Frans van der Helm ()

Abstract:
Brain activity results in small electric potentials, which can be recorded with electrodes on the skin over the scalp, i.e. electroencephalography (EEG). Current EEG systems can have 128 or more electrodes, giving an indication of the patterns and location of brain activity. Since EEG is only measured at the skin surrounding the brain, the exact origin of the measured signals remains unknown. Source localization is a technique to localize the origin of the signal inside the brain and to reconstruct the signal at the source. One of the applications of EEG source localisation is the study of neural activity of people who have suffered from stroke and, more specifically, the brain regions involved in motor control. A better understanding of how brain activity changes following a stroke potentially leads to more effective rehabilitation programs [1]. However EEG source localization relies on a high signal-to-noise ratio at the electrodes to accurately reconstruct a source within the brain [2]. Conventionally, EEG is measured during evoked potentials, where typically hundreds of events (e.g. repeated button presses or finger taps) are recorded, averaged and used for source localization [2]. Our goal is to develop a novel approach which improves the signal-to-noise ratio and, as such, improves the localization accuracy and reduces the number of required recordings. There are several ways to increase the signal-to-noise ratio of the EEG recordings. An initial increase is achieved by using a state-of-the-art EEG amplifier with properly shielded electrodes. Our novel approach applies perturbations using a robotic manipulator while the subject performs a motor task such as maintaining a position or a target force level. The perturbation signal will be a periodic multisine signal (a signal consisting of multiple sinusoids) which only contains power at defined frequencies, allowing for an increase in power at these frequencies and therewith the signal-to-noise ratio, while the non-excited frequencies allow to estimate the signal distortion due to nonlinearities [3].